After pretraining on image inpainting, we evaluate the few-shot sematic segmentation performance of the models. We construct three few-shot segmentation datasets by selecting training and validation images from CelebA-Faces, ADE-Cars, and LSUN-Cats as in [1]}. The model is trained using cross-entropy loss. We measure mIoU over the validation set. More details about the experiments are deferred to the Appendix.
<TABLE>